Stress combinations and their interactions in plants database: a one-stop resource on combined stress responses in plants

Multiblock NIR and MIR spectralprint through AComDim to evaluate the effects of growing site, harvest season, and clone on yerba mate leaves composition

The composition of yerba mate implies significant potential in the food, pharmaceutical, and cosmetic industries, which requires standardization of the raw material. This study explores the simultaneous influence of growing sites, harvest seasons, and clones on the spectralprint of leaves through near-infrared (NIR) and mid-infrared (MIR) spectroscopy coupled with ANOVA Common Dimensions (AComDim) multivariate analysis. MIR spectroscopy identifies only the main effects of growing site and harvesting season, and the interaction between these factors. The NIR spectralprint identifies all main effects and interactions. Growing site and harvesting season individually account for approximately 7 % of the variance in the chemical composition of yerba mate, with their interaction contributing with 5.7 %. Clonal variation significantly affects the spectral profile with approximately 4 % variance, which allowed the identification of clones with the highest chemical divergence. The study demonstrates that biospectroscopics and chemometrics can enhance yerba mate quality through clonal selection and optimized agricultural practices.

Mechanisms of plant acclimation to multiple abiotic stresses

Plants frequently encounter a range of abiotic stresses and their combinations. Even though stresses rarely occur in isolation, research on plant stress resilience typically focuses on single environmental stressors. Plant responses to abiotic stress combinations are often distinct from corresponding individual stresses. Factors determining the outcomes of combined stresses are complex and multifaceted. In this review, we summarize advancements in our understanding of the mechanisms underlying plant responses to co-occurring (combined and sequential) abiotic stresses, focusing on morphological, physiological, developmental, and molecular aspects. Comprehensive understanding of plant acclimation, including the signaling and response mechanisms to combined and individual stresses, can contribute to the development of strategies for enhancing plant resilience in dynamic environments.

Integrated analysis of transcriptomics and metabolomics and high-throughput amplicon sequencing reveals the synergistic effects of secondary metabolites and rhizosphere microbiota on root rot resistance in Psammosilene tunicoides

Psammosilene tunicoides is a plant with significant medicinal and ecological value, exhibiting remarkable medicinal properties, particularly in anti-inflammatory, antioxidant, and immune-regulatory effects. Root rot is one of the primary diseases affecting Psammosilene tunicoides, leading to a significant decline in its quality. In this study, we utilized an integrated analysis of transcriptomics, metabolomics, high-throughput amplicon sequencing, and culturomics for revealing the difference of healthy samples (CH) and diseased samples (CD) and studying the defense mechanism of P. tunicoides in resisting root rot. Transcriptome revealed distinct patterns of gene expression between healthy root samples (HR) and diseased root samples (DR) of P. tunicoides. The Key enzyme genes involved in triterpene (e.g., HMGS, DXS, SQS, CYP450) and flavonoid (e.g., PAL, CHS, CHI) biosynthesis pathways were significantly upregulated in DR. Consistent results were observed in the metabolomic analysis, where triterpene saponins and flavonoids were more highly accumulated in DR than in HR. Microbiome data indicated a significant enrichment of Actinobacteria at the genus level in the rhizosphere soil of diseased samples (DS) compared to healthy samples (HS) while the mostly beneficial growth-promoting bacterial groups were found in DR root endophytes, including Enterobacter, Pseudomonas, Klebsiella, Stenotrophomonas, and Bacillus. Through culturomics, we successfully isolated and identified over 220 bacterial strains from the rhizosphere soil of diseased samples, including genera including Bacillus, Streptomyces, Cupriavidus, Pseudomonas, and Paenarthrobacter. Notably, the strain Pseudomonas sp., which was significantly enriched in DR, exhibited a clear antagonistic effect against Fusarium oxysporum. Co-occurrence network analysis of multi-omics data revealed that many Actinomycetes positively correlated with triterpenoid and flavonoid compounds and their key genes. Therefore, we conclude that these secondary metabolites may could resist pathogen invasion directly or serve as an "intermediate medium" to recruit growth-promoting microorganisms to resistant the root rot. This study investigates the "Plant-Microbe" interaction network associated with root rot resistance in P. tunicoides, revealing its significant implications for the ecological cultivation and management of this species.

Genomic prediction with NetGP based on gene network and multi-omics data in plants

Genomic selection (GS) is a new breeding strategy. Generally, traditional methods are used for predicting traits based on the whole genome. However, the prediction accuracy of these models remains limited because they cannot fully reflect the intricate nonlinear interactions between genotypes and traits. Here, a novel single nucleotide polymorphism (SNP) feature extraction technique based on the Pearson-Collinearity Selection (PCS) is firstly presented and improves prediction accuracy across several known models. Furthermore, gene network prediction model (NetGP) is a novel deep learning approach designed for phenotypic prediction. It utilizes transcriptomic dataset (Trans), genomic dataset (SNP) and multi-omics dataset (Trans + SNP). The NetGP model demonstrated better performance compared to other models in genomic predictions, transcriptomic predictions and multi-omics predictions. NetGP multi-omics model performed better than independent genomic or transcriptomic prediction models. Prediction performance evaluations using several other plants' data showed good generalizability for NetGP. Taken together, our study not only offers a novel and effective tool for plant genomic selection but also points to new avenues for future plant breeding research.

Aluminum alleviates iron deficiency chlorosis by interfering with phosphorus homeostasis in rice (Oryza sativa L.)

Rice (Oryza sativa L.) is a staple food for more than half of the human population. Rice plants are cultivated in several different environments, and face various abiotic stresses, including nutritional imbalance in soils. The ionome, the inorganic composition of an organism, is known to be tightly regulated, as changes in concentration of one element affect concentrations of others. Iron (Fe) is an essential element that is involved in redox reactions, nitrogen metabolism and chlorophyll synthesis. The hallmark of Fe deficiency in plants is leaf chlorosis, a phenotype known to be alleviated by deficiencies of other elements, such as phosphorus (P). Aluminum (Al) is abundant in soils and limits plant growth in acidic soils. Despite its well-established detrimental effects, Al has been proposed to have a positive effect on growth for some species, but little is known about this phenomenon. Here we aim to understand whether Al affects Fe homeostasis in rice. We found that Al alleviated Fe deficiency-induced chlorosis. +Al-Fe treatment decreased expression of Fe deficiency marker genes and partially recovered photosynthesis. We also observed that Al induced expression of a P deficiency marker gene, and addition of excess P to nutrient solution reversed effects of Al on chlorosis. Our data show that Al alleviates Fe deficiency-induced chlorosis, and suggests that this occurs indirectly by inducing P deficiency in leaves.

Metabolome profiling dissects the oat (Avena sativa L.) innate immune response to Pseudomonas syringae pathovars

One of the most important characteristics of successful plant defence is the ability to rapidly identify potential threats in the surrounding environment. Plants rely on the perception of microbe-derived molecular pattern chemicals for this recognition, which initiates a number of induced defence reactions that ultimately increase plant resistance. The metabolome acts as a metabolic fingerprint of the biochemical activities of a biological system under particular conditions, and therefore provides a functional readout of the cellular mechanisms involved. Untargeted metabolomics was applied to decipher the biochemical processes related to defence responses of oat plants inoculated with pathovars of Pseudomonas syringae (pathogenic and non-pathogenic on oat) and thereby identify signatory markers that are involved in host or nonhost defence responses. The strains were P. syringae pv. coronafaciens (Ps-c), P. syringae pv. tabaci, P. syringae pv. tomato DC3000 and the hrcC mutant of DC3000. At the seedling growth stage, metabolic alterations in the Dunnart oat cultivar (tolerant to Ps-c) in response to inoculation with the respective P. syringae pathovars were examined following perception and response assays. Following inoculation, plants were monitored for symptom development and harvested at 2-, 4- and 6 d.p.i. Methanolic leaf extracts were analysed by ultra-high-performance liquid chromatography (UHPLC) connected to high-definition mass spectrometry. Chemometric modelling and multivariate statistical analysis indicated time-related metabolic reconfigurations that point to host and nonhost interactions in response to bacterial inoculation/infection. Metabolic profiles derived from further multivariate data analyses revealed a range of metabolite classes involved in the respective defence responses, including fatty acids, amino acids, phenolic acids and phenolic amides, flavonoids, saponins, and alkaloids. The findings in this study allowed the elucidation of metabolic changes involved in oat defence responses to a range of pathovars of P. syringae and ultimately contribute to a more comprehensive view of the oat plant metabolism under biotic stress during host vs nonhost interactions.

Comprehensive approaches to heavy metal bioremediation: Integrating microbial insights and genetic innovations

The increasing contamination of ecosystems with heavy metals (HMs) due to industrial activities raises significant jeopardies to environmental health and human well-being. Addressing this issue, recent advances in the field of bioremediation have highlighted the potential of plant-associated microbiomes and genetically engineered organisms (GEOs) to mitigate HMs pollution. This review explores recent advancements in bioremediation strategies for HMs detoxification, with particular attention to omics technologies such as metagenomics, metabolomics, and metaproteomics in deepening the understanding of microbial interactions and their potential for neutralizing HMs. Additionally, Emerging strategies and technologies in GEOs and microorganism-aided nanotechnology have proven to be effective bioremediation tools, particularly for alleviating HM contamination. Despite the promising strategies developed in laboratory settings, several challenges impede their practical application, including ecological risks, regulatory limitations, and public concerns regarding the practice of genetically modified organisms. A comprehensive approach that involves interdisciplinary research is essential to enhance the efficacy and safety of bioremediation technologies. This approach should be coupled with robust regulatory frameworks and active public engagement to ensure environmental integrity and societal acceptance. This review underscores the importance of developing sustainable bioremediation strategies that align with ecological conservation goals and public health priorities.

Enhancing Tolerance to Combined Heat and Drought Stress in Cool-Season Grain Legumes: Mechanisms, Genetic Insights, and Future Directions

The increasing frequency of concurrent heat and drought stress poses a significant challenge to agricultural productivity, particularly for cool-season grain legumes, including broad bean (Vicia Faba L.), lupin (Lupinus spp.), lentil (Lens culinaris Medik), chickpea (Cicer arietinum L.), grasspea (Lathyrus sativus L.), pea (Pisum sativum L.), and common vetch (Vicia sativa L.). These legumes play a vital role in sustainable agricultural systems due to their nitrogen-fixing ability and high nutritional value. This review synthesizes current knowledge of the impacts and tolerance mechanisms associated with combined heat and drought stresses in these crops. We evaluate physiological and biochemical responses to combined heat and drought stress, focusing on their detrimental effects on growth, development, and yield. Key genetic and molecular mechanisms, such as the roles of osmolytes, antioxidants, and stress-responsive genes, are explored. We also discuss the intricate interplay between heat and drought stress signaling pathways, including the involvement of Ca2+ ions, reactive oxygen species, transcription factor DREB2A, and the endoplasmic reticulum in mediating stress responses. This comprehensive analysis offers new insights into developing resilient legume varieties to enhance agricultural sustainability under climate change. Future research should prioritize integrating omics technologies to unravel plant responses to combined abiotic stresses.

Special Issue "Advances in the Physiology of Primary and Secondary Plant Metabolism Under Abiotic and Biotic Stress"

One of the most relevant areas of biology is the study of plant adaptation processes to the action of various stress factors of abiotic and biotic nature, which is reflected in the works of molecular biologists, geneticists, microbiologists, plant physiologists, and biochemists, as well as biotechnologists [...].

Unmasking complexities of combined stresses for creating climate-smart crops

Understanding the complex challenges that plants face from multiple stresses is key to developing climate-ready crops. We highlight the significance of the Stress Combinations and their Interactions in Plants database (SCIPdb) for studying the impact of stress combinations on plants and the importance of aligning thematic research programs to create crops aligned with achieving sustainable development goals.

Integrated stress responses in okra plants (cv. ''Meya']: unravelling the mechanisms underlying drought and nematode co-occurrence

BACKGROUND

Climate change threatens sub-Saharan Africa's agricultural production, causing abiotic and biotic stressors. The study of plant responses to joint stressors is crucial for understanding molecular processes and identifying resilient crops for global food security. This study aimed to explore the shared and tailored responses of okra plants (cv. ''Meya'), at the biochemical and molecular levels, subjected to combined stresses of drought and Meloidogyne incognita infection.

DESIGN

The study involved 240 okra plants in a completely randomized design, with six treatments replicated 20 times. Okra plants were adequately irrigated at the end of every 10-days water deficit that lasted for 66 days (D). Also, the plants were infected with M. incognita for 66 days and irrigated at 2-days intervals (R). The stresses were done independently, in sequential combination (D before R and R before D) and concurrently (R and D). All biochemical and antioxidant enzyme assays were carried out following standard procedures.

RESULTS

Significant reductions in leaf relative water content were recorded in all stressed plants, especially in leaves of plants under individual drought stress (D) (41.6%) and plants stressed with root-knot nematode infection before drought stress (RBD) (41.4%). Malondialdehyde contents in leaf tissues from plants in D, nematode-only stress (RKN), drought stress before root-knot nematode infection (DBR), RBD, and concurrent drought-nematode stress (RAD) significantly increased by 320.2%, 152.9%, 186.5%, 283.7%, and 109.6%, respectively. Plants in D exhibited the highest superoxide dismutase activities in leaf (147.1% increase) and root (105.8% increase) tissues. Catalase (CAT) activities were significantly increased only in leaves of plants in D (90.8%) and RBD (88.9%), while only roots of plants in D exhibited a substantially higher CAT activity (139.3% increase) in comparison to controlled plants. Okra plants over-expressed NCED3 and under-expressed Me3 genes in leaf tissues. The NCED3 gene was overexpressed in roots from all treatments, while CYP707A3 was under-expressed only in roots of plants in RBD and RKN. CYP707A3 and NCED3 were grouped as closely related genes, while members of the Me3 genes were clustered into a separate group.

CONCLUSION

The biochemical and molecular responses observed in okra plants (cv. ''Meya') subjected to combined stresses of drought and Meloidogyne incognita infection provide valuable insights into enhancing crop resilience under multifaceted stress conditions, particularly relevant for agricultural practices in sub-Saharan Africa facing increasing climatic challenges.

A machine learning algorithm for the automatic classification of Phytophthora infestans genotypes into clonal lineages

Premise

The prompt categorization of Phytophthora infestans isolates into described clonal lineages is a key tool for the management of its associated disease, potato late blight. New isolates of this pathogen are currently classified by comparing their microsatellite genotypes with characterized clonal lineages, but an automated classification tool would greatly improve this process. Here, we developed a flexible machine learning-based classifier for P. infestans genotypes.

Methods

The performance of different machine learning algorithms in classifying P. infestans genotypes into its clonal lineages was preliminarily evaluated with decreasing amounts of training data. The four best algorithms were then evaluated using all collected genotypes.

Results

mlpML, cforest, nnet, and AdaBag performed best in the preliminary test, correctly classifying almost 100% of the genotypes. AdaBag performed significantly better than the others when tested using the complete data set (Tukey HSD P < 0.001). This algorithm was then implemented in a web application for the automated classification of P. infestans genotypes, which is freely available at https://github.com/cpatarroyo/genotypeclas.

Discussion

We developed a gradient boosting-based tool to automatically classify P. infestans genotypes into its clonal lineages. This could become a valuable resource for the prompt identification of clonal lineages spreading into new regions.

Metabolites-induced co-evolutionary warfare between plants, viruses, and their associated vectors: So close yet so far away

Agriculture and global food security encounter significant challenges due to viral threats. In the following decades, several molecular studies have focused on discovering biosynthetic pathways of numerous defensive and signaling compounds, as key regulators of plant interactions, either with viruses or their associated vectors. Nevertheless, the complexities of specialized metabolites mediated plant-virus-vector tripartite viewpoint and the identification of their co-evolutionary crossroads toward antiviral defense system, remain elusive. The current study reviews the various roles of plant-specialized metabolites (PSMs) and how plants use these metabolites to defend against viruses. It discusses recent examples of specialized metabolites that have broad-spectrum antiviral properties. Additionally, the study presents the co-evolutionary basis of metabolite-mediated plant-virus-insect interactions as a potential bioinspired approach to combat viral threats. The prospects also show promising metabolic engineering strategies aimed at discovering a wide range of PSMs that are effective in fending off viruses and their related vectors. These advances in understanding the potential role of PSMs in plant-virus interactions not only serve as a cornerstone for developing plant antiviral systems, but also highlight essential principles of biological control.

Baking bad: plants in a toasty world with necrotrophs

Rising global temperatures pose a threat to plant immunity, making them more susceptible to diseases. The impact of temperature on plant immunity against biotrophic and hemi-biotrophic pathogens is well documented, while its effect on necrotrophs remains poorly understood. We venture into the uncharted territory of necrotrophic fungal pathogens in the face of rising temperatures. We discuss the role of the plant hormones salicylic acid (SA) and jasmonic acid (JA) in providing resistance to necrotrophs and delve into the temperature sensitivity of the SA pathway. Additionally, we explore the repercussions of increased temperatures on plant susceptibility to necrotrophs. We put forward a research agenda with an experimental framework aimed at providing a comprehensive understanding of how plants and pathogens adapt to increasing temperatures.

The plant disease triangle facing climate change: a molecular perspective

Variations in climate conditions can dramatically affect plant health and the generation of climate-resilient crops is imperative to food security. In addition to directly affecting plants, it is predicted that more severe climate conditions will also result in greater biotic stresses. Recent studies have identified climate-sensitive molecular pathways that can result in plants being more susceptible to infection under unfavorable conditions. Here, we review how expected changes in climate will impact plant-pathogen interactions, with a focus on mechanisms regulating plant immunity and microbial virulence strategies. We highlight the complex interactions between abiotic and biotic stresses with the goal of identifying components and/or pathways that are promising targets for genetic engineering to enhance adaptation and strengthen resilience in dynamically changing environments.

Biological Nano-Agrochemicals for Crop Production as an Emerging Way to Address Heat and Associated Stresses

Climate change is a global problem facing all aspects of the agricultural sector. Heat stress due to increasing atmospheric temperature is one of the most common climate change impacts on agriculture. Heat stress has direct effects on crop production, along with indirect effects through associated problems such as drought, salinity, and pathogenic stresses. Approaches reported to be effective to mitigate heat stress include nano-management. Nano-agrochemicals such as nanofertilizers and nanopesticides are emerging approaches that have shown promise against heat stress, particularly biogenic nano-sources. Nanomaterials are favorable for crop production due to their low toxicity and eco-friendly action. This review focuses on the different stresses associated with heat stress and their impacts on crop production. Nano-management of crops under heat stress, including the application of biogenic nanofertilizers and nanopesticides, are discussed. The potential and limitations of these biogenic nano-agrochemicals are reviewed. Potential nanotoxicity problems need more investigation at the local, national, and global levels, as well as additional studies into biogenic nano-agrochemicals and their effects on soil, plant, and microbial properties and processes.

Drought: A context-dependent damper and aggravator of plant diseases

Drought dynamically influences the interactions between plants and pathogens, thereby affecting disease outbreaks. Understanding the intricate mechanistic aspects of the multiscale interactions among plants, pathogens, and the environment-known as the disease triangle-is paramount for enhancing the climate resilience of crop plants. In this review, we systematically compile and comprehensively analyse current knowledge on the influence of drought on the severity of plant diseases. We emphasise that studying these stresses in isolation is not sufficient to predict how plants respond to combined stress from both drought and pathogens. The impact of drought and pathogens on plants is complex and multifaceted, encompassing the activation of antagonistic signalling cascades in response to stress factors. The nature, intensity, and temporality of drought and pathogen stress occurrence significantly influence the outcome of diseases. We delineate the drought-sensitive nodes of plant immunity and highlight the emerging points of crosstalk between drought and defence signalling under combined stress. The limited mechanistic understanding of these interactions is acknowledged as a key research gap in this area. The information synthesised herein will be crucial for crafting strategies for the accurate prediction and mitigation of future crop disease risks, particularly in the context of a changing climate.

Creating Climate-Resilient Crops by Increasing Drought, Heat, and Salt Tolerance

Over the years, the changes in the agriculture industry have been inevitable, considering the need to feed the growing population. As the world population continues to grow, food security has become challenged. Resources such as arable land and freshwater have become scarce due to quick urbanization in developing countries and anthropologic activities; expanding agricultural production areas is not an option. Environmental and climatic factors such as drought, heat, and salt stresses pose serious threats to food production worldwide. Therefore, the need to utilize the remaining arable land and water effectively and efficiently and to maximize the yield to support the increasing food demand has become crucial. It is essential to develop climate-resilient crops that will outperform traditional crops under any abiotic stress conditions such as heat, drought, and salt, as well as these stresses in any combinations. This review provides a glimpse of how plant breeding in agriculture has evolved to overcome the harsh environmental conditions and what the future would be like.

Transcriptomics, proteomics, and metabolomics interventions prompt crop improvement against metal(loid) toxicity

The escalating challenges posed by metal(loid) toxicity in agricultural ecosystems, exacerbated by rapid climate change and anthropogenic pressures, demand urgent attention. Soil contamination is a critical issue because it significantly impacts crop productivity. The widespread threat of metal(loid) toxicity can jeopardize global food security due to contaminated food supplies and pose environmental risks, contributing to soil and water pollution and thus impacting the whole ecosystem. In this context, plants have evolved complex mechanisms to combat metal(loid) stress. Amid the array of innovative approaches, omics, notably transcriptomics, proteomics, and metabolomics, have emerged as transformative tools, shedding light on the genes, proteins, and key metabolites involved in metal(loid) stress responses and tolerance mechanisms. These identified candidates hold promise for developing high-yielding crops with desirable agronomic traits. Computational biology tools like bioinformatics, biological databases, and analytical pipelines support these omics approaches by harnessing diverse information and facilitating the mapping of genotype-to-phenotype relationships under stress conditions. This review explores: (1) the multifaceted strategies that plants use to adapt to metal(loid) toxicity in their environment; (2) the latest findings in metal(loid)-mediated transcriptomics, proteomics, and metabolomics studies across various plant species; (3) the integration of omics data with artificial intelligence and high-throughput phenotyping; (4) the latest bioinformatics databases, tools and pipelines for single and/or multi-omics data integration; (5) the latest insights into stress adaptations and tolerance mechanisms for future outlooks; and (6) the capacity of omics advances for creating sustainable and resilient crop plants that can thrive in metal(loid)-contaminated environments.

When two negatives make a positive: the favorable impact of the combination of abiotic stress and pathogen infection on plants

Combined abiotic and biotic stresses modify plant defense signaling, leading to either the activation or suppression of defense responses. Although the majority of combined abiotic and biotic stresses reduce plant fitness, certain abiotic stresses reduce the severity of pathogen infection in plants. Remarkably, certain pathogens also improve the tolerance of some plants to a few abiotic stresses. While considerable research focuses on the detrimental impact of combined stresses on plants, the upside of combined stress remains hidden. This review succinctly discusses the interactions between abiotic stresses and pathogen infection that benefit plant fitness. Various factors that govern the positive influence of combined abiotic stress and pathogen infection on plant performance are also discussed. In addition, we provide a brief overview of the role of pathogens, mainly viruses, in improving plant responses to abiotic stresses. We further highlight the critical nodes in defense signaling that guide plant responses during abiotic stress towards enhanced resistance to pathogens. Studies on antagonistic interactions between abiotic and biotic stressors can uncover candidates in host plant defense that may shield plants from combined stresses.